9 March 2010 Comparison of myocardial motion estimation methods based on simulated echocardiographic B-mode and RF data
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Abstract
In this paper, we combine a ventricular kinematic model and an ultrasound simulation model in order to simulate the echocardiographic imaging process. In addition to its capability to generate raw RF data, when compared to previous echocardiography simulation models, the result achieves more realistic B-Mode images. Several echocardiography parameters were taken into account including central frequency, apodization, number of elements in the array, speed of sound, and number of scatterers. The proposed improvements are due to the use of a shift-variant Point Spread Function (PSF) and more accurate cardiac motion assumptions. One attribute of the simulator is also that it provides the groundtruth vector field of actual "ventricular deformations'' which may be used to strictly validate motion estimation and myocardial elastography algorithms. The paper presents the first application of optical flow to normalized data in piece-wise segments of RF images. Different optical flow motion estimation techniques such as Lucas-Kanade, Horn-Schunck, Brox et al., Black and Anandan, and Block Matching (BM) were applied to the simulated B-mode images and RF data. The estimated motion fields from the RF data as well as the B-mode images were validated with the ground-truth motion fields derived from the simulator. The validation results show that the Brox et al. method performs better than other motion estimation techniques when applied to B-Mode and RF data. Also, as intuitively expected, use of RF data results in more accurate displacement fields than when B-mode images alone are used.
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Vahid Tavakoli, Vahid Tavakoli, Jamie Kemp, Jamie Kemp, Buddha Dawn, Buddha Dawn, Marcus Stoddard, Marcus Stoddard, Amir A. Amini, Amir A. Amini, } "Comparison of myocardial motion estimation methods based on simulated echocardiographic B-mode and RF data", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 76260N (9 March 2010); doi: 10.1117/12.845698; https://doi.org/10.1117/12.845698
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